Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA

Elias Krainski, Virgilio Gómez-Rubio, Haakon Bakka, Amanda Lenzi, Daniela Castro Camilo, Daniel Simpson, Finn Lindgren, Håvard Rue

Research output: Book/ReportBook

Abstract / Description of output

Modeling spatial and spatio-temporal continuous processes is an important and challenging problem in spatial statistics. Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA describes in detail the stochastic partial differential equations (SPDE) approach for modeling continuous spatial processes with a Matérn covariance, which has been implemented using the integrated nested Laplace approximation (INLA) in the R-INLA package. Key concepts about modeling spatial processes and the SPDE approach are explained with examples using simulated data and real applications.
Original languageEnglish
Place of PublicationNew York
PublisherTaylor & Francis
Number of pages298
ISBN (Electronic)9780429031892
ISBN (Print)9781138369856
DOIs
Publication statusPublished - 31 Dec 2018

Fingerprint

Dive into the research topics of 'Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA'. Together they form a unique fingerprint.

Cite this